SHELDON1 is the first true hybridization of NLP machine reading and the Semantic Web. It extracts RDF data from text using a machine reader: the extracted RDF graphs are compliant to Semantic Web and Linked Data. It goes further and applies Semantic Web practices and technolo- gies to extend the current human-readable web. The input is represented by a sentence in any language. SHELDON includes different capabilities in order to extend machine reading to Semantic Web data: frame detection, topic ex- traction, named entity recognition, resolution and corefer- ence, terminology extraction, sense tagging and disambigua- tion, taxonomy induction, semantic role labeling, type in- duction, sentiment analysis, citation inference, relation and event extraction, nice visualization tools which make use of the JavaScript infoVis Toolkit and RelFinder. A demo of SHELDON can be seen and used at http://wit.istc.cnr. it/stlab-tools/sheldon.
Extracting knowledge from text using SHELDON, a semantic holistic framEwork for LinkeD ONtology data
Tipo Pubblicazione:
Contributo in atti di convegno
Source:
24th International Conference on World Wide Web (WWW2015), pp. 235–238, Florence, Italy, 18-22/05/2015
info:cnr-pdr/source/autori:Recupero, Diego Reforgiato; Nuzzolese, Andrea Giovanni; Consoli, Sergio; Presutti, Valentina; Peroni, Silvio; Mongiovì, Misael/congresso_nome:24th International Conference on World Wide Web (WWW2015)/congresso_luogo:Florence, It
Date:
2015
Resource Identifier:
http://www.cnr.it/prodotto/i/366593
https://dx.doi.org/10.1145/2740908.2742842
info:doi:10.1145/2740908.2742842
http://www.scopus.com/record/display.url?eid=2-s2.0-84968593217&origin=inward
Language:
Eng